Python finds its applications far and wide across the digital world. Be it web development, data science, data analytics, AI, and whatnot. Even in the case of Computer Vision, Python is the only language that comes to mind. Especially when it comes to the subdomain of facial recognition, industrial applications are far-reaching. This technology is being used to validate human faces through images and videos. And to support it, there are numerous libraries in Python that power face detection, recognition, tracking, and authentication.
Let’s look at some of these well-established libraries. face_recognition remains the simplest face recognition library with a model which has 99.38% accuracy. We also have the faceswap library, which is developed by Deepfakes. Powered by Keras, Tensorflow, and Python, it is a leading free and Open-Source multi-platform software that runs on all major operating systems. FaceNet is another face recognition system that’s been developed by researchers at Google. It takes the person’s face as input and outputs a vector of 128 numbers representing the most important features of a face. It leverages triplet loss along with deep convolutional networks to achieve the highest order of accuracy. The following is a comprehensive list of the best open-source libraries: